Byron Wallace, Phd

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En provenance du cours de Johns Hopkins University

Introduction to Systematic Review and Meta-Analysis

1029 notes

Johns Hopkins University

Introduction to Systematic Review and Meta-Analysis

1029 notes

We will introduce methods to perform systematic reviews and meta-analysis of clinical trials. We will cover how to formulate an answerable research question, define inclusion and exclusion criteria, search for the evidence, extract data, assess the risk of bias in clinical trials, and perform a meta-analysis. Upon successfully completing this course, participants will be able to: - Describe the steps in conducting a systematic review - Develop an answerable question using the “Participants Interventions Comparisons Outcomes” (PICO) framework - Describe the process used to collect and extract data from reports of clinical trials - Describe methods to critically assess the risk of bias of clinical trials - Describe and interpret the results of meta-analyses

À partir de la leçon

Searching Principles and Bias Assessment

In this module we will look at finding the evidence, as well as key sources, search strategy, and assessing the risk of bias.

Byron Wallace, Phd2:00

Rencontrer les enseignants

Tianjing Li, MD, MHS, PHD
Assistant Professor, Epidemiology
Bloomberg School of Public Health
Kay Dickersin, PhD
Professor, Epidemiology
Bloomberg School of Public Health

I was at Tufts University and I happened to get connected

with Thomas Trikalinos and Joseph Lau, and Chris Schmid.

And at the time I was working on machine learning and

natural language processing stuff.

And it occurred to all of us jointly, along with my advisor, Carla Brodley,

that perhaps we could expedite some of the processes that were being done manually

in evidence synthesis using machine learning and natural image processing.

So ever since then I've been working on that.

The aspect that's received the most attention is probably on

the screening side.

So this is where you're identifying the literature,

the evidence to be included in the systematic review that you're performing.

And there's been a lot of work that's looked at using automation techniques, and

in particular, automatic classification techniques to expedite that process.

And I think those technologies are actually pretty well established.

And I think the general consensus is that you can reduce the labor by about half

without sacrificing sensitivity or recall to the relevant evidence,

which is really important.

So these tools, we've developed some of them and other people as well,

including for example James Thomas and his group.

Our stuff you can find at Abstrackr, so it's free to use and it's open source.

But again, that's just one one instance,

and I think generally these kinds of technologies have been helpful.

The other bit that's kind of more emerging, I think,

are methods for automating the actual extraction of structured information

from publications describing the results of trials and other findings.

And this I think is still in the research phases, but it's certainly something that

I'm working on and a bunch of other people are as well.

But from my own plug I would say we have this thing called RobotReviewer that we've

been working on that does a lot of this and

tries to automate things like risk bias appraisal.

Julian Higgins has also done similar things with one of his students.

So I think there's a lot of interest in this space generally.

So it'll be exciting to see where it all goes.

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